The implementation of Advanced Measurement Infrastructure – AMIs, in the installation of each customer of the electricity utility helps operators of the electricity distribution network to achieve optimization of network utilization, improve availability and reduce costs.

In 2020, Colombia has made considerable progress in formulating and approving policies and creating the legal frameworks needed to implement the advanced measurement infrastructure. In this formulation process many interesting conclusions have emerged in :

• the benefits identified are several and apply to both users, distribution network operators (OR) marketers, and almost anyone who wants to know the characteristics of energy consumption in a sector, region or in any geographic region.
• For the benefits obtained, it is very convenient to install this infrastructure on each user’s meters, without generating cost to end users.
• The information manager would have the possibility to know in detail the consumption behavior of all users under his influence. That is why you must establish special security conditions for access to such information.

In this article we want to focus the analysis on the opportunities provided by installing each advanced power meter to the Network Operator (OR),

Different ways to achieve optimization in the operation of the power grid with the implementation of AMI to THE OR.

There are many benefits to the network operator. Most of them are based on the collection, integration, analysis and simulation of information around network behavior and forecasting network demand and operation.

1. reducing losses. By being able to simulate and understand the distribution of energy along the infrastructure and possible to carry out an energy balance by infrastructure and in this way identify in which elements the losses occur.
2. Capacity usage analysis by system, additionally allows to identify networks more accurately at maximum capacity and generate power quality problems at the tip of the system. By this same study, it is very possible to identify efficient investments to improve capacity problems. In this way, investments that would otherwise have to be made can be deferred.
3. Reduced operating and maintenance costs. Maintenance may be performed only when the equipment or system has conditions requiring maintenance. Even with the right artificial intelligence models, it is possible to foresee with high certainty when a team will fail and achieve maintenance optimization.
4. Implement an efficiency control module. Corresponds to the measurement of key indicators or KPIs: Comparing between actual and expected data, as well as ensuring that it between tolerance ranges with adequate statistical control. In general, efficiency refers to the relationship between inputs and outputs. or it can also be given by loss indices Better online monitoring and very close knowledge of the operation of the network. Often the operating conditions of a system vary greatly from design to reality, with the correct information it is very possible to monitor linearly the operation of the network, trigger alarms, and improve energy quality, increase reliability and stabilize operating conditions to standards.
5. Predictive maintenance or anticipation of failures. Based on the use of predictive monitoring tools, the condition of the assets is continuously monitored, it is intended to avoid unexpected equipment failure. It seems impossible, but with the collection of the right data it is possible to identify the indications of potential failures from the analysis of the previous failures.
6. A reduction in the unavailability time associated with the repair, by making it in advance conditions and being able to have planned materials, inputs,
   qualified human resources, spare parts, among others.
7. Asset health. Depending on the type of asset the overall operating status of each subsite is qualified, It uses as input data a specialized Sensorica, usually linked to the manufacturer’s specifications and technical process analysis. Using an internationally recognized methodology developed by Toronto Hydro. supports the definition of an asset risk-based maintenance strategy.
8. Risk assessment. It consists of associating the consequences of a computer failure; valued in monetary terms to the assets, usually based on the money generated by the energy it carries. In this way, it is possible to consider the risk per asset without simply multiplying the probability of failure by its consequences. In other words, you can assess the probability of failure of each of the system components, which in addition to the impact or cost of failure valuation.

1. Health Index Monitoring

2.